The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...
Execution-driven simulators are often used for power/energy and performance evaluation. Simulators can provide semantic details but they provide insufficient speed and accuracy f...
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Abstract. The paper introduces a new receiver-based active end-toend measurement technique, called the Single-Double Unicast Probing (SDUP), to estimate the rate of losses which oc...
We study the tradeoffs between the number of measurements, the signal sparsity level, and the measurement noise level for exact support recovery of sparse signals via random noisy ...